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[![Documentation Status](https://readthedocs.org/projects/zj-pynet/badge/?version=latest)](https://zj-pynet.readthedocs.io/zh_CN/latest/?badge=latest) [![standard-readme compliant](https://img.shields.io/badge/standard--readme-OK-green.svg?style=flat-square)](https://github.com/RichardLitt/standard-readme) [![Conventional Commits](https://img.shields.io/badge/Conventional%20Commits-1.0.0-yellow.svg)](https://conventionalcommits.org) [![Commitizen friendly](https://img.shields.io/badge/commitizen-friendly-brightgreen.svg)](http://commitizen.github.io/cz-cli/)

[英文版本(English version)](./README.EN.md)

> 基于Numpy的深度学习库
基于`Numpy`的深度学习实现,模块化设计保证模型的轻松实现,适用于深度学习初级研究人员的入门

[使用示例](https://zj-pynet.readthedocs.io/zh_CN/latest/%E7%A4%BA%E4%BE%8B/)

![](./docs/imgs/loss.png)

![](./docs/imgs/acc.png)

## 内容列表

- [背景](#背景)
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## 安装

`PyNet`需要以下必备条件

* `python3.x`
* `numpy`
* `opencv3.x`
```
# 文档工具依赖
$ pip install -r requiremens.txt
# PyNet库依赖
$ cd pynet
$ pip install -r requirements.txt
```

## 用法

参考[example](https://github.com/zjZSTU/PyNet/tree/master/examples)文件夹下的示例代码

完整版本参考[releases](https://github.com/zjZSTU/PyNet/releases)

已实现网络模型(位于[pynet/models](https://github.com/zjZSTU/PyNet/tree/master/pynet/models)文件夹):
有两种文档使用方式

* `2`层神经网络
* `3`层神经网络
* `LeNet-5`
* `AlexNet`
* `NIN`
1. 在线浏览文档:[PyNet](https://zj-pynet.readthedocs.io/zh_CN/latest/)

已实现网络层(位于[pynet/nn](https://github.com/zjZSTU/PyNet/tree/master/pynet/nn)文件夹)
2. 本地浏览文档,实现如下

* 卷积层
* 全连接层
* 最大池化层
* `ReLU`
* 随机失活
* `Softmax`
* 交叉熵损失
* 全局平均池化层
```
$ git clone https://zj-pynet.readthedocs.io/zh_CN/latest/
$ cd PyNet
$ mkdocs serve
```
启动本地服务器后即可登录浏览器`localhost:8000`

## 版本更新日志

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